ECG Artifact Reduction System

ABSTRACT

An ECG signal processing system which removes the CPR-induced artifact from measured ECG signals obtained during the administration of CPR.

This application is a continuation of U.S. application Ser. No.14/196,981, filed Mar. 4, 2014, now abandoned, which is a continuationof U.S. application Ser. No. 13/460,454, filed Apr. 30, 2012, now U.S.Pat. No. 8,666,480, which is a continuation of U.S. application Ser. No.12/906,722, filed Oct. 18, 2010, now abandoned, which is a continuationof U.S. application Ser. No. 11/939,476, filed Nov. 13, 2007, now U.S.Pat. No. 7,818,049, which is a continuation of U.S. application Ser. No.10/901,862, filed Jul. 29, 2004, now U.S. Pat. No. 7,295,871, which is acontinuation of U.S. application Ser. No. 10/057,540, filed Jan. 23,2002, now U.S. Pat. No. 6,865,413, which is a divisional application ofU.S. application Ser. No. 09/188,211 filed on Nov. 9, 1998, now U.S.Pat. No. 6,390,996.

FIELD OF THE INVENTIONS

The present invention relates to a device for aiding in theadministration of cardiopulmonary resuscitation (CPR). Morespecifically, certain aspects of the invention relate to devices formonitoring CPR efforts and facilitating better CPR administration.

BACKGROUND OF THE INVENTIONS

Various U.S. patent documents disclose sensors for assisting in theadministration of CPR. For example, U.S. Pat. No. 5,589,639 (D′Antonioet al.) discloses a force sensing system for a CPR device whichgenerates an intelligible output signal corresponding to a forceparameter. The CPR device utilizes a signal indicative of the forcebeing applied to the recipient's chest.

U.S. Pat. No. 5,496,257 (Kelly) discloses an apparatus for assisting inthe application of CPR. The device rests on the recipient's chest. Chestcompression forces are monitored by the device in order to ascertain therate of compression and blood flow. This information is activelyprovided to the rescuer to prompt proper administration of CPR.

Various devices are disclosed which assist in the timing of theapplication of CPR, including U.S. Pat. No. 5,626,618 (Ward et al.) andU.S. Pat. No. 4,863,385 (Pierce). The '618 patent discloses, among otherthings, an electrode combination for cardiac pacing and cardiacmonitoring in association with a bladder for use in the patient'sesophagus for improving artificial circulation as a result of CPR. The'385 patent discloses a CPR sequencer which comprises a compact,portable, computer-controlled device, which provides timing and sequenceguidance for helping a rescuer in the application of CPR to a recipient.

Each year there are more than 300,000 victims of cardiac arrest. Currentconventional techniques for CPR introduced in 1960 have had limitedsuccess both inside and outside of the hospital, with only about 15%survival rate. Accordingly, the importance of improving resuscitationtechniques cannot be overestimated. In the majority of cardiac arrests,the arrest is due to ventricular fibrillation, which causes the heart toimmediately stop pumping blood. To treat ventricular fibrillation,defibrillation is administered which involves the delivery of a highenergy electric shock to the thorax to depolarize the myocardium, and toallow a perfusing rhythm to restart. If, however, more than a fewminutes pass between the onset of ventricular fibrillation and thedelivery of the first defibrillation shock, the heart may be so deprivedof metabolic substrates that defibrillation is unsuccessful.

The role of CPR is to restore the flow of oxygenated blood to the heart,which may allow defibrillation to occur. A further role of CPR is torestore the flow of oxygenated blood to the brain, which may preventbrain damage until the heart can be restarted. Thus, CPR is critical inthe treatment of a large number of patients who fail initialdefibrillation, or who are not candidates for defibrillation.

Various studies show a strong correlation between restarting the heartand higher levels of coronary blood flow. To restart the heart, ifinitial defibrillation fails (or is not indicated), coronary flow mustbe provided. With well-performed CPR, together with the use ofepinephrine, brain blood flow probably reaches 30-50% of normal.Myocardial blood flow is much more limited, however, in the range of5-20% of normal. In patients, heart restarting has been shown tocorrelate with the pressure gradient between the aorta and the rightatrium, obtained between compressions (i.e., the coronary perfusionpressure). CPR, when applied correctly, is designed to provide asufficient amount of coronary perfusion pressure by applying asufficient amount of chest compression force. Unfortunately, however,studies indicate that CPR is performed correctly only part of thetime—approximately 50% of the time according to a study conducted on 885patients. Hoeyweghen et al., “Quality and Efficacy of Bystander CPR,”Resuscitation 26 (1993), pp. 47-52. The same study showed that long-termsurvival, defined as being awake 14 days after CPR, was 16% in patientswith correct CPR, but only 4% when CPR was performed with less chestcompression (p<0.05). Thus, properly administered CPR can increasesurvival rates.

Not only is the correct application of CPR critical to the survival ofthe CPR recipient, but when initial defibrillation is unsuccessful, oris not indicated, it can be essential that CPR be applied immediately.The sooner persons are resuscitated, the more likely they will survivelong-term with preservation of neurologic function. When initialresuscitative efforts at the scene of an arrest fail to restore nativecardiac function, it is often the practice to transport the patient tothe hospital with the hope that better CPR can be performed under thesupervision of a physician. A number of studies have shown, however,that it is quite rare for a patient who is not resuscitated in the fieldto be resuscitated in the hospital, and survive with meaningfulneurologic function. Even invasive interventions used in hospitals, suchas open chest cardiac massage, have failed to improve survival rates,probably due to irreversible organ damage produced by prolonged schemaduring transportation.

The American Heart Association (AHA) published guidelines specify thatchest compression during CPR should be done at a rate of 80-100compressions per minute at a depth of 1.5 to 2 inches. During CPRcourses, instrumented mannequins are generally used that measure theamount of chest compression a student applies. It is then up to thestudent to apply similar chest compressions in an emergency situation,without feedback, relying only on the feel and look of the compressions.Since there is no feedback, and since relatively small changes in theamount of compression can affect perfusion pressure, it is notsurprising that CPR is often performed incorrectly.

As described above, various types of devices have been provided to helpgive the rescuer administering CPR feedback. However, these devices donot measure chest displacement. Rather, they measure compression forceas a result of the applied CPR. This is problematic since with clinicalCPR there is considerable variation in the compliance of differentpatients' chests, such that similar compression forces producesubstantially different chest displacements in different patients.

Gruben et al. disclose in their article entitled “SternalForce-Displacement Relationship During Cardiopulmonary Resuscitation,”Journal of Biomedical Engineering, Volume 115 (May 1993), p. 195, theuse of mechanical linkages incorporating position-sensing transducers tomeasure chest displacement during clinical CPR. However, this mechanismpresents problems in general clinical environments, such as delays insetup and awkward handling.

While resuscitation is in progress, it is vital that physicians,paramedics, and other healthcare professionals administering CPR becontinuously aware of changes in the patient's electrocardiogram (ECG),particularly the heart rhythm. An incorrect assessment of the heartrhythm can lead to administration of inappropriate therapy orwithholding of appropriate therapy. The chest compressions associatedwith CPR, however, introduce artifacts in the measured ECG signal thatmake its interpretation difficult. The rather inadequate approachgenerally used to facilitate ECG interpretation during CPR isintermittent cessation of chest compressions to provide a period ofartifact-free ECG acquisition. Problems occur with this approach. Forone, there is a loss of hemodynamic support when chest compressions arestopped. In addition, the ECG remains difficult or impossible tointerpret once chest compressions are resumed. Accordingly, suddenchanges in rhythm may not be appreciated until after a substantialdelay. In addition, since survival from cardiac arrest has been shown tobe related to blood flow generated during CPR, and since interruption ofchest compressions will reduce blood flow, survival may very well becompromised by these interruptions.

The outcome of CPR may be improved if there were a means for reducingthe CPR-induced artifacts present in an ECG signal in a manner whichwould allow the correct interpretation of the ECG without interruptingchest compressions applied during CPR. E. Witherow has performed studieswhich demonstrate that CPR-induced artifacts are due primarily tochanges in the half-cell potential of electrodes, caused by theirmechanical disturbance. This was published in a thesis entitled A Studyof the Noise in the ECG During CPR, M.S. thesis, the Johns HopkinsUniversity (1993), the content of which is hereby expressly incorporatedby reference herein in its entirety.

There is a need for compact, portable, and economic tools for monitoringCPR efforts, aiding in the correct administration of CPR, and otherwiseincreasing the success of resuscitation efforts, e.g., by removingCPR-induced artifacts from ECG signals so CPR does not need to bestopped in order to obtain a good ECG reading.

SUMMARY

The devices described herein aid in the proper application of CPR invarious situations in order to substantially improve the survival rateof CPR recipients. They also improve upon resuscitation techniquesinvolving the concurrent administering of CPR and monitoring of thepatient's ECG, and more particularly, the patient's heart rhythm. Thesystem provides for measuring and prompting chest compressions tofacilitate the effective administration of CPR.

A hand-held CPR chest compression monitor accurately measures the rateand depth of chest compressions during the administration of CPR. Thedevice signals the rescuer to prompt correct compressions. It requires aminimum amount of set-up time, is intuitive in its operation, and iseasy to use. The device would preferably be small in size, have a lowweight, and be inexpensive to manufacture and distribute.

In addition, a hand-held CPR chest compression monitor is provided withan integral defibrillator and/or data storage and retrieval components.The system provides for concurrently administering CPR with the aid of ahand-held CPR chest compression monitor and obtaining ECG signals fromthe CPR recipient. It also provides a device for removingcompression-induced artifacts found in the ECG signals during CPR toallow accurate ECG and heart rhythm readings without stopping CPR.

The system (which may be in the form of a hand-held device), alsomeasures and prompts chest compressions to facilitate the effectiveadministration of CPR by a rescuer. The system comprises a displacementdetector for producing an output signal indicative of a displacement ofa CPR recipient's chest toward the CPR recipient's spine. A signalingmechanism provides signals directing a chest compression force beingapplied to the chest and a frequency of compressions to bring andmaintain the frequency of compressions within desired frequency range.It also brings and maintains the chest displacement within a desireddistance range.

The displacement detector comprises a motion detector for determining anamount of CPR induced motion of the chest in relation to the spine. Aconverter converts an output signal produced by the motion detector intoa distance value. The signaling mechanism comprises a mechanism forcomparing the distance value to a desired range of distance values, andfor signaling directions regarding chest compression force and frequencyin accordance with whether the value falls within the desired range ofdistance values.

A hand-held CPR chest compression monitor such as that provided abovemay be used in association with an automated chest compressionmechanism. In this context the device controls the manner in which theautomated chest compression mechanism applies chest compressions to arecipient. It thereby allows effective administration of CPR to therecipient in accordance with certain chest displacement and compressionfrequency parameters. Such a hand-held CPR chest compression monitor maybe further provided in association with an ECG monitor.

An ECG signal enhancer is provided for subtracting or otherwisesuppressing chest compression-induced artifacts from the ECG signal. Thesignal enhancer facilitates reading of the ECG signal, and moreparticularly, facilitates reading of the heart rhythm of the CPRrecipient without the need to stop CPR.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a hand-held CPR chest compressionmonitor;

FIG. 2 is a waveform diagram comparing measured and calculated signalscaused by manual compressions of a simulated chest of a CPR recipient;

FIG. 3 is a perspective view of a layout of a hand-held module formonitoring CPR chest compressions;

FIG. 4 is a side view of the module illustrated in FIG. 3;

FIGS. 5-7 each show a rescuer administering CPR to a CPR recipientutilizing a CPR monitoring device;

FIG. 8 shows a CPR recipient coupled to various resuscitation assistanceapparatuses;

FIG. 9 is a flow chart of the process utilized by the chest compressionmonitor illustrated in FIG. 1 in order to convert a detectedacceleration signal into a displacement value;

FIG. 10 is a model of a system comprising a CPR recipient receiving CPRwhile an ECG monitor connected to the CPR recipient generates a measuredECG signal e_(m)(t);

FIG. 11 is a model for the conversion of a measured ECG signal e_(m)(t)to a processed measured ECG signal e_(m)′(t);

FIG. 12 is a waveform diagram showing the respective waveforms a_(r)(t),e_(m)(t), a_(p)(t), e_(m)′(t);

FIG. 13 illustrates that the system that gives rise to the measured ECGsignal e_(m)(t) can be modeled as the sum of the true ECG e(t) and anartifact waveform a(t);

FIG. 14 illustrates a signal processing method for removing aCPR-induced artifact;

FIG. 15 shows a block diagram representation of an ECG signal processorutilizing a fast Fourier transform technique; and

FIG. 16 shows a block diagram representation of an ECG signal processorutilizing a recursive least squares analysis technique.

DETAILED DESCRIPTION OF THE INVENTIONS

FIG. 1 is a schematic representation of a hand-held CPR chestcompression monitor 10 for measuring the rate and depth of chestcompressions during the administration of CPR. The monitor 10 is aspecific implementation of a monitoring system for measuring andprompting chest compressions to facilitate the effective administrationof cardiopulmonary resuscitation (CPR). The system comprises adisplacement detector and a signaling mechanism. The displacementdetector produces and outputs a displacement signal indicative of thedisplacement of a CPR recipient's chest toward the recipient's spine.The signaling mechanism provides chest compression indication signalsdirecting a chest compression force applied to the chest and a frequencyof compressions to bring and maintain the frequency and chestdisplacement parameters within desired ranges. The monitoring system maybe further provided with a tilt compensator comprising a tilt sensormechanism outputting a tilt compensation signal indicative of the extentof tilt of the device. The system may further include an adjuster foradjusting the displacement value calculated from the measuredacceleration signal in accordance with the output tilt compensationsignal.

A hand-held CPR chest compression monitor 10 is provided. It comprises adisplacement detector comprising an accelerometer 12 coupled to amicroprocessor 28 via an interface 26. The illustrated interface 26 maycomprise a parallel or serial interface which may be internal (wheremicroprocessor 28 is provided as part of one integral device) orexternal (where microprocessor 28 is provided as a separate device). Thesignaling mechanism comprises an audible indicator (i.e., a loudspeaker) 18, which has an input connected to microprocessor 28 viainterface 26. A DC voltage power supply 20 is connected between a switch22 and ground, and provides a DC voltage +V for powering the variouscomponents of the monitor 10, including the above-noted accelerometer 12and audible indicator 18. Tilt compensation devices are provided whichinclude a first gyro 24 and a second gyro 25. They each include outputsconnected to microprocessor 28 via interface 26.

While the monitor uses an audible indicator, other types of indicatorsmay be used in addition or as an alternative. For example, the indicatormay comprise a vibrating mechanism, visual indicators (e.g., blinkingLEDs), and so on.

The monitor 10 determines chest displacement from a double integrationof an acceleration signal produced by accelerometer 12. Microprocessor28 is provided to handle the calculations needed to perform the variousfunctions of the monitor 10, including the double integration of theacceleration signal. The accelerometer 12 will preferably comprise ahigh-quality, inexpensive accelerometer, such as the Analog DevicesADXL05.

The ADXL05 accelerometer comprises a complete acceleration measurementsystem provided on a single monolithic IC. It comprises a polysiliconsurface micro-machined sensor and signal conditioning circuitry whichimplement a force-balanced control loop. The accelerometer is capable ofmeasuring both positive and negative acceleration to a maximum level ofplus or minus 5 g. The sensor comprises 46 unit cells and a common beam.The unit cells make up a differential capacitor, which comprisesindependent fixed plates and central plates attached to the main beamthat moves in response to an applied acceleration. These plates form twocapacitors, connected in series. The sensor's fixed capacitor plates aredriven differentially by two 1 MHz square waves: the two square waveamplitudes are equal but are 180 degrees out of phase from one another.When at rest, the values of the two capacitors are the same, andtherefore, the voltage output at their electrical center (i.e., at thecenter plate) is 0. When there is an applied acceleration, the commoncentral plate or “beam” moves closer to one of the fixed plates whilemoving farther from the other. This creates a miss-match in the twocapacitances, resulting in an output signal at the central plate. Theamplitude of the output signal varies directly with the amount ofacceleration experienced by the sensor.

A self-test may be initiated with the ADXL05 accelerometer by applying aTTL “high” level voltage (>+2.0Vdc) to the accelerometer self-test pin,which causes the chip to apply a deflection voltage to the beam whichmoves it an amount equal to −5 g (the negative full-scale output of thedevice).

In operation, accelerometer 12 of compression monitor 10 will move invarious directions not limited to a simple vertical-only movement. Inother words, monitor 10 will tilt on the CPR recipient's chest duringthe administration of CPR, which will cause the linear motion indicatedby accelerometer 12 to be corrupted by non-linear tilt-inducedmovements. Accordingly, the tilt sensor mechanism facilitates thedetermination of the true displacement of the chest in relation to therecipient's spine without errors caused by tilting of the device withrespect to the chest. First gyro 24 produces an angular velocity signalindicating the measured angular velocity around a first horizontallongitudinal axis, and second gyro 25 outputs an angular velocity signalindicating the measured angular velocity around a second horizontallongitudinal axis positioned perpendicular to the first longitudinalaxis. These angular velocity signals integrated to obtain angulardisplacement signals, which can be used to correct the measured lineardisplacement for tilt of the monitor 10.

First and second gyros 24 and 25 comprise a Murata Gyrostar(piezoelectric gyroscope (ENC05E)). This commercially available gyro isapproximately 20×8×5 mm in size, and is designed for large-volumeapplications such as stabilizing camcorder images. This gyro uses theCoriolis principle, which means that a linear motion with a rotationalframework will have some force that is perpendicular to that linearmotion. The Coriolis force is detected and converted to a voltage outputby piezoelectric transducer elements mounted on a prism bar. The voltageoutput is proportional to the detected angular velocity. In theillustrated embodiment, the two gyros are driven at slightly differentfrequencies in order to avoid interference.

Interface 26, in addition to a serial or parallel interface, may furthercomprise AJD and D/A converters, including a D/A converter for drivingaudio transducer 18 to indicate the amount of displacement and to promptCPR at the correct rate (80-100 compressions per minute). The outputfrom accelerometer 12 is routed through an AID converter provided aspart of interface 26 for digitization and subsequent analysis bymicroprocessor 28. Similarly, the output from each of first and secondgyros 24 and 25 is routed to microprocessor 28 via an A/D converterprovided as part of interface 26.

Microprocessor 28 is provided as part of a hand-held integrated modulecomprising monitor 10. As an alternative, a separate computer such as alap top computer may be provided which is coupled to interface 26(serving as an external interface) of the monitor 10.

Further information, regarding other types of inertial proprioceptivedevices utilizing accelerometers and gyros, is provided by C. Verplaetsein an article entitled “Inertial Proprioceptive Devices:Self-Motion-Sensing-Toys and Tools,” IBM Systems Journal, Vol. 35, Nos.3 and 4 (1996) pages 639-650, the content of which is hereby expresslyincorporated herein by reference in its entirety.

FIG. 2 shows signals produced by a simulated recipient chest assembly.The simulated chest assembly was comprised of a spring connecting ablock to a firmly supported base. Linear bearings inside the block rodeon a shaft to keep the block aligned vertically and to facilitatevertical movement of the block. A damper was coupled to the block toslow the movement of the block to simulate chest compliance. Verticaldisplacement of the block was measured by a position transducer (LVDT).A force transducer was attached to the top of the aluminum block, andprovided signals indicative of the output forces as a result of CPR-likecompressions. The assembly was calibrated and designed to closely mimicthe visco-elastic properties of the human chest. The force transducerwas calibrated with standard weights and the displacement transducer wascalibrated with a ruler. An accelerometer (ANALOG DEVICES® ADXL-05) wasmounted on a circuit board with appropriate biasing and filteringcomponents, and the circuit board was attached to an aluminum holder.The accelerometer assembly was placed on a the simulated chest andmanual compressions were applied.

FIG. 2 shows a comparison of actual displacement (measured by LVDT) anddisplacement calculated using the acceleration signals from theaccelerometer assembly, during manual compressions of the simulatedchest. The acceleration signals were doubly integrated and were plottedwith the measured displacement and acceleration. The signals' waveformsare displayed with respect to an abscissa representing a progression intime and an ordinate axis representing a value of either displacement inmillimeters or acceleration, g. The waveforms include an accelerationsignal 30, a measured distance signal 32, and a calculated distancesignal 34. FIG. 2 demonstrates the closeness of fit of the calculatedand measured displacement, especially the maximum displacements, whichis an important parameter.

FIGS. 3 and 4 show an exemplary mechanical layout of a hand-held modulecomprising a compression monitor 10 implemented in accordance with theschematic diagram shown in FIG. 1. The module 11 comprises a circularbase 36 having an outer flange portion 37. Mounted on base 36 is acircuit board 38. Circuit board 38 is fixed to base 36 by means offasteners 40. A plurality of components are mounted directly on circuitboard 38, including first and second gyros 24 and 25, accelerometer 12,indicator 18, power source 20, and interface 26.

The module is roughly 3 inches in diameter and 0.5 inches in height.FIG. 3 shows first and second gyros 24 and 25 mounted at right angles toeach other on circuit board 38, which measure the angular velocityaround each of their respective longitudinal axes. The illustratedaccelerometer 12 is packaged in a TO-100 package (a 10 pin can), wherethe axis of sensitivity to acceleration (vertical) is perpendicular tothe plane of circuit board 38. Accelerometer 12 is attached to a rightangle support 43 which provides electrical connections with circuitboard 38, as well as a rigid mounting surface.

FIGS. 5-7 show various implementations of a hand-held device which maybe utilized in connection with the compression monitor 10 disclosedherein.

FIG. 5 illustrates a rescuer 46 administering CPR to a recipient 47. Therescuer's hands are placed in contact with the recipient's chest at theproper location. A compression monitor 10 is attached to one of therescuer's wrists at the point which is proximate to the point at whichrescuer 46 is exerting force on the recipient's chest during CPR. Themonitor 10 comprises a mount coupled a housing portion of the monitor.The mount comprises a releasable fixing mechanism, i.e., a band 48 forreleasably fixing housing portion 50 (containing the various componentsof monitor 10, such as those shown in FIG. 1) to the rescuer's 46extremity (wrist).

In FIG. 6, a compression monitor 10 comprises a housing 50, and acompression force translating piece 52 positioned thereunder forfocusing the force exerted by rescuer 46 to a desired area downwardlyagainst the chest of the CPR recipient, in the direction facing therecipient's spine. The hand-held monitor 10 may comprise a cable 44 forcoupling monitored signals to a computing device (not shown) which isseparate from the handheld device. In the alternative, a processor maybe integrally provided within housing 50, in which case cable 44 wouldnot be necessary.

In FIG. 7, hand-held monitor 10 comprises a unitary disc-like housing50, upon which a rescuer 46 places his or her hands. Each of theversions of the compression monitor 10 shown in FIGS. 6 and 7 thusprovides on top of housing 50 a receiving portion for directly receivinga downwardly acting force from the hands of rescuer 46 proximate to apoint at which rescuer 46 is exerting force on the recipient's chestduring CPR. Depending upon whether housing 50 already contains amicroprocessor, an external cable 44 may be provided for coupling theelectrical components within housing 50 to an external signal monitoringsystem or a computer. ECG electrodes 54 are coupled to respective ECGsignal lines 56 and an ECG monitor device (not shown).

A mechanism (e.g., a self-contained ECG display) may be provided withinthe illustrated compression monitor 10 for displaying and/or processingthe ECG signals; accordingly, alternatively, ECG signal lines 56 may becoupled to compression monitor 10.

In operation, the compression monitor 10 of either of the embodimentsshown in FIGS. 5-7 will facilitate the effective administration of CPRby producing a displacement-indicative signal indicative of thedisplacement of the recipient's chest toward the recipient's spine.Specifically, the audible indicator provided within device 10 ismodulated to indicate when the proper chest displacement is achieved.That is, when a chest displacement in a desired range is achieved byrescuer 46, the audible indicator will output a modulated signal havinga first pitch, while if the displacement is out of range, the frequencyof the modulated signal will be at a second pitch. The amplitude of theaudible indication may be pulsed to coincide with the desired frequencyof chest compressions. Alternatively, the audible indicator can provide,together, with appropriate signal processing components, verbalindications to the rescuer 46, i.e., serving as voice prompts to therescuer. As another alternative, an audio transducer may be providedwhich outputs a beeping sound to prompt the user to compress at theproper rate.

FIG. 8 shows a CPR recipient connected to various resuscitation-aidingapparatuses, including an automated constricting device 59 forautomatically administering CPR to the recipient. Automated constrictingdevice 59, more specifically, applies inwardly radial forces against therecipient's chest in order to cause a desired chest displacement in thedirection toward the recipient spine at a desired chest compressionfrequency.

Additional apparatuses connected to the recipient include a ventilatormask 58 coupled to an air tube 60, ECG electrodes and corresponding ECGsignal lines 56, defibrillation electrodes 62, and a CPR chestcompression monitor 10′ coupled to a cable 44, for carrying signalsgenerated thereby, including a detected acceleration signal.

The overall assembly facilities the resuscitation of a recipient 47 inan automated fashion. Such a set up can be particularly useful invarious situations, for example, including the case where the recipientis being carried in an ambulance vehicle. Resuscitation efforts could becontinued while the recipient is being transported, thus increasing thechance of survival by providing resuscitation efforts as soon aspossible while transporting the recipient to the hospital.

As illustrated, the recipient is hooked up to a ventilation apparatuscomprising a ventilator mask 58, which will allow respiration efforts tobe administered. The patient's ECG and associated heart rhythminformation can be monitored by ECG signal lines 56 coupled to an ECGmonitor device (not shown). CPR can be automatically administered byautomated constricting device 59. Timely defibrillation can beadministered with the use of defibrillation electrodes 62 coupled viadefibrillation lines 64 to a defibrillation device (not shown). Theautomated constricting device 59 can be controlled by signals producedby compression monitor 10′ so that the proper compression forces areapplied to the recipient's chest at the appropriate frequency.

In addition, the acceleration signal produced by compression monitor 10′can be retrieved via cable 44 and used to process the ECG signalobtained via ECG signal lines 56 concurrently with the administration ofCPR. More specifically, when CPR is administered, the ECG signal may beaffected and thus include a CPR-induced artifact. An ECG processor,which will be further described below, may be provided to process theECG signal so as to remove the CPR-induced artifact and render theresulting processed ECG signal meaningful and intelligible.

The automated constricting device 59 may comprise, for example, the CPRvest apparatus disclosed in the commonly-assigned co-pending patentapplication Ser. No. 09/188,211 filed Mar. 29, 1999 in the name of Dr.Henry Halperin, or it may comprise an automated CPR system as disclosedin U.S. Pat. No. 4,928,67 (Halperin et al). The content of each of thesereferences is hereby expressly incorporated herein by reference in theirentirety.

In the assembly shown in FIG. 8, an automated constriction controller(not shown) is provided together with the automated constricting devicefor applying CPR to the recipient 47 by applying a constricting force tothe chest of the recipient 47 under control of the automated controller.The automated controller receives the chest compression indicationsignals from compression monitor 10′, and, in accordance with the chestcompression indication signals, controls the force and frequency ofconstrictions applied to the CPR recipient's chest.

FIG. 9 is a flow chart illustrating a process for converting theacceleration and tilt signals produced by the compression monitor 10shown in Figure I into a displacement-indicative signal, and forcalibrating the conversions. The process may be performed by amicroprocessor 28 as shown in FIG. 1.

In a first step S2, the acceleration signal is converted into a lineardisplacement x. Then, in step S4, the angular velocity signals output byeach of first and second gyros 24 and 25 are converted into respectiveangular displacements theta, and theta₂. In step S6, the displacement xis compensated for the tilting, thus producing a tilt-compensated lineardisplacement value xt which is equal to x+ax(theta₁)+bx(theta₂).

During each chest compression cycle (usually 600-700 ms), the devicewill come to rest twice: at the zenith and nadir of the compression.These two time points may be easily identified since the verticalacceleration at these times will be 0, and there will be a change in thedirection of the velocity. Accordingly, at step S8, a determination ismade as to whether the device is at the zenith or nadir. If it is, thelinear displacement conversion is calibrated at step S 10. If not, theprocess will return to step S2. In calibrating the linear displacementconversion, at step S 10, measurements are made at the rest point tore-calibrate the system and eliminate the components v₀, x₀ from theequation (noted below) utilized to convert acceleration in to lineardisplacement x.

Algorithms are well known for converting an acceleration signal (from anaccelerometer) into linear displacement and for converting an angularvelocity signal (from gyros) into an angular displacement. In general,inertial navigation systems may determine position and orientation fromthe basic kinematic equations for transitional and rotational motion.The orientation of an object, given a sensed rotational rate, w, duringeach time step t, is given by:

θ=θ₀ +wt   (1)

where q equals the orientation angle, t equals the time step and w isthe rotational rate output by a gyroscope.

Similarly, position is found with the transitional kinematic equation:

x=x ₀ +v ₀ t+(0.5)at ²,   (2)

where x equals position, v equals velocity and a equals acceleration,output by an accelerometer.

Motion and position are estimated with equations, (1) and (2).Alternatively, motion and position may be estimated using a Kalmanfilter state estimation algorithm. Once the time-dependent motions andpositions of the system are estimated, a pattern recognition scheme suchas a neural network, hidden Markov model, or matched filter may beperformed with that motion data.

The true vertical displacement x^(t) is estimated as a combination ofone translation and two angular displacement x, theta₁, and theta₂. Itis expected that within the expected angular deviation range of +/−30degrees from vertical a simple equation (3) will work:

x _(t) =x+ax(theta₁)+bx(theta₂)   (3)

Coefficients a and b are determined empirically using best linear fitmethods. A more complex non-linear model may also be used.

In the event thermal drift is a factor, additional circuitry may beprovided as part of the compression monitor for thermal compensation.

While resuscitation is in progress, it is highly desirable that healthcare personnel be continuously aware of changes in the patient's ECG, inparticular the patient's heart rhythm. Incorrect assessment of the heartrhythm can lead to improper therapy. However, when CPR is administered,CPR-introduced artifacts will be present in the measured ECG signal thatmake interpretations difficult. FIGS. 10-16 provide various systemmodels, analysis waveform diagrams, and proposed ECG processingembodiments for addressing this problem.

As shown in FIG. 10, it can be assumed that the measured ECG signale_(m)(t) obtained on ECG signal lines 56 is equal to the sum of the trueECG signal e(t) and the true CPR noise signal, a (the CPR-inducedartifact). A subsystem is created into which the measured ECG signale_(m)(t) is input and from which a processed measured ECG signale_(m)′(t), absence the CPR-induced artifact, is output.

As an initial approach toward eliminating the CPR induced artifact, aband pass filter 66 as shown in FIG. 11 may be utilized. In thisapproach, the measured ECG e_(m)(t) is viewed as the superposition of atrue ECG e and CPR noise. Filter 66 selectively preserves as much of theECG signal as possible, while suppressing the artifact as well aspossible. The problem with this approach is that it is difficult toseparate the true ECG from the CPR-induced artifact since components ofeach of those signals coexist in the same portions of the frequencydomain.

FIG. 12 shows several waveforms pertinent to the processing of aCPR-affected ECG signal. A first waveform a_(r)(t) represents ameasurable signal that “represents” the CPR-induced artifact. Thatsignal may comprise a force, acceleration, distance, velocity, motion,or vest signal, each of which represents some aspect of the CPR-inducedartifact. In the illustrated embodiment, the signal a_(r)(t) comprisesthe acceleration signal produced by the accelerometer 12 of the deviceshown in FIG. 1.

The next waveform is the measure ECG signal e_(m)(t), measured duringCPR. The following waveform a_(p)(t) is the predicted artifact. The lastwaveform e_(m)′(t), is the processed measured ECG signal, which has beenprocessed to remove the CPR-induced artifact. The processed measured ECGsignal e_(m)′(t) shown in FIG. 12 was produced using linear predictivefiltering as will be described below.

FIG. 13 shows that the system that gives rise to the measured ECGsignal, e_(m)(t), can be modeled as the sum of the true ECG, e(t), andan artifact waveform, a(t). When the true ECG and ECG artifactcomponents overlap in both time and frequency domains it is neverthelesspossible to distinguish the two if a separate signal, correlated withthe artifact, is available. Specifically, the true CPR noise signal a(t)is treated as the output of a linear system {tilde over (h)} perturbedby a measurable accelerometer signal input a_(r)(t).

FIG. 14 illustrates a signal processing method for removing aCPR-induced artifact. Removing the artifact is accomplished byidentifying the linear transfer system h that transforms theacceleration signal a_(r)(t) into the waveform composed of theartifactual components, i.e., a(t), in the measured ECG, e_(m)(t). Oncethis system is identified, the artifactual component can be predicted,using linear predictive filtering, by taking the output a_(p)(t) of asimulated system {tilde over (h)}, using the acceleration signala_(r)(t) as the input. When this linearly predicted signal a_(p)(t) issubtracted from the measured ECG e_(m)(t), the resulting signal is theestimated true ECG. The estimated true ECG is shown in FIG. 14 as theprocessed ECG signal, e_(m)′(t), in the output of the system. Theprocessed ECG signal e_(m)′(t) is produced by utilizing the overlap andadd technique.

FIG. 15 shows the system identification process 70 shown in FIG. 14. Thesystem identification block 70 comprises a correlated signal inputa_(r)(t) 86 and a non-correlated signal input e_(m)(t) 88. Correlatedsignal input 86 is input to a first FFT 76, while non-correlated signalinput 88 is input through a second FFT 78. The output of first FFT 76 isinput to a autospectrum calculator 80 and to cross-spectrum calculator82. The output of second FFT 78 is input to cross-spectrum calculator82.

The output of the first FFT 76 is the frequency domain representation ofthe measured signal a_(r)(t) and the output of the second FFT 78 is thefrequency domain representation of the measured ECG signal e_(m)(t).Autospectrum calculator 80 outputs Saa which is the input signal'sautospectrum, while cross-spectrum 82 outputs Sae which is thecross-spectrum between the observed input and output signals. These canbe computed using Fourier transform techniques, for example, asdisclosed by Jenkins et al. “Spectral Analysis and its Applications,”Holden Day, Oakland, Calif. (1968), and R. D. Berger, “Analysis of theCardiovascular Control System Using Broad-Band Stimulation,” Ph. D.Thesis, MIT (1987), the content of each of which is hereby expresslyincorporated herein by reference in their entirety.

The input signals autospectrum Saa is then input into the denominatorinput of a complex divider 84, while the cross-spectrum Sae (between theobserved input and output signals) is input to the numerator input ofdivider 84. Divider 84 performs complex division on its input signals inorder to produce at its output 90 a complex representation of theestimated transfer function {tilde over (H)}. The transfer function{tilde over (H)} can be updated periodically from new short segments ofinput signals, which may include the acceleration signal output by theaccelerometer and the measured ECG signal.

Instead of system {tilde over (H)} being a linear system, a non-linearsystem may be estimated instead and used to subtract the CPR-inducedartifact from the measured ECG signal.

Once {tilde over (H)}, which is in the frequency domain, is determinedit is input into an inverse fast Fourier transform to produce the systemtransfer function {tilde over (h)}, which is the same system transferfunction in the time domain. Using a microprocessor, the system transferfunction {tilde over (h)} then acts on a_(r)(t) to produce the predictedartifact signal a_(p)(t), as shown in FIG. 14. Finally, the sum ofe_(m)(t) and a_(p)(t) produces the filtered true signal e_(m)′(t), asalso shown in FIG. 14.

As an alternative to the systems shown in FIGS. 14 and 15, a recursiveleast squares analysis (RLS) subsystem 90 may be provided as shown inFIG. 16.

In accordance with the recursive least squares method, each time a newdata sample is input to each of the inputs of the subsystem, therecursive model is modified on an ongoing basis. Techniques forutilizing the recursive least squares method to produce an RLS subsystem90 as shown in FIG. 16 are known in the art. For example, reference maybe made to L. Ljung et al., “Theory and Practice of RecursiveIdentification,” the MIT Press, Cambridge, Mass. (1983), the content ofwhich is hereby expressly incorporated by reference herein in itsentirety.

The artifact accelerometer signal a_(r)(t) is inputted with the measuredECG signal e_(m)(t) into the RLS system to produce the output filteredtrue signal e_(m)′(t) The following is an example program listing whichmay form the basis for employing an RLS subsystem:

x: input (acceleration a_(r)(t)), y: measured output (e_(m)(t)), z:predicted output (e_(m)′(t)) linpred ( x, y, z, npts, m, n) float *x, *Y, *z; long npts; int m, n; /* m: MA order, n: AR order */ { double phi[MAXARMALEN], theta [MAXARMALEN], 1 [MAXARMALEN]; double p [MAXARMALEN][MAXARMALEN], alpha=1.0 double array 1 [MAXARMALEN], array2[MAXARMALEN], c; double mat[MAXARMALEN][MAXARMALEN],mat2[MAXARMALEN][MAXARMALEN], int i, j, k;  for (k = 0; k<m+n; k++) {  theta[k] = 0;   for( j=o; j<m+n; j++) {    if( j −−k )     p[k] [j]-LARGE;    else     p[k] [j] 0;   }  }  for (i−0; 1<m+n, i++)   z [i] =y[i];  for ( i = m+n; i<npts; i++) {   j=0;   for( k= 1; k<=n; k++) {   phi [j] = −y[i−k];    j++;   }   for( k= 1; k<=m; k++) {    phi[j] =x[i−k];    j++;   }   mat_array_mult ( p, phi, array 1, m+n);  arrayt_array_mult ( phi, array 1, &c, m+n);   array_k_mult ( array 1,1/alpha + c, 1, m+n);   arrayt_mat_mult ( phi, p, array2, m+n );  array_arrayt_mult (1, array2, mat1, m+n);   mat_mat_subtract (p, mat1,mat2, m+n)   mat_copy (mat2, p, m+n);   arrayt_array_mult ( theta, phi,&c, m+n);   array_k_mult ( 1, y[i]−c, array 1, m+n );   array_array_add( theta, array1, array2, m+n);   array_copy ( array2, theta, m+n );  arrayt_array_mult ( theta, phi, &c, m+n);   z[i] = c;  printf(“%2f/n”, c );  } } mat_array_mult (a, b, c, dim) double a [ ][MAXARMALEN], *b, *c; int dim; { int i, j;  for (i = 0; i<dim; i++) {  c[i] = 0   for (j−0; j<dim; j++)    c[i] + = a[i][j]j *b[j];  } }array_array_mult (a, b, c, dim) double *a, *b, *c; int dim; [ int i;  *c= 0;  for ( i=o; i<dim; i++)   *c + a[i] *b[i]; } array_mat_mult (a, b,c, dim) double *a, b[ ] [MAXARMALEN], *c; int dim; { int i,j;  for i=o;i<dim; i++)  {   c[i] − 0;   for( j=o;j<dim;j++)    c[i] + = a[i]*b[j][i]  } } array_arrayt_mult ( a, b, c, dim) double *a, *b, c[ ][MAXARMALEN]; int dim; { int i,j;;  for ( i=o; i<dim; i++)  for ( j=o;j<dim; j++)    c[i][j] − a[i]*b[j]; } array_k_mult ( a, b, c, dim)double *a, b, *c; int dim; { int i;  for i=0 i<dim; i++)   c[i] =a[i]*b; } mat_mat_subtract ( a, b, c, dim) double a[ ][MAXARMALEN], b[ ][MAXARMALEN], c[ ] [MAXARMALEN]; int dim; { int i,j;  for ( i=o; i<dim;i++)   for j=0; j<dim; j++)    c[i][j] = a[i][j] − b[i][j]; }array_array_add( a, b, c, dim) double *a, *b, *c; int dim; { int i;  for( i=o; i<dim; i++)   c[i] = a[i]+b[i]; } mat_copy (a, b, dim) double a[][MAXARMALEN], b[ ][MAXARMALEN]; int dim; { int i, j;  for (i=o; i<dim;i++)   for (j=0; j<dim; j+l)    b[i][j] = a[i][j]; } array_copy ( a, b,dim) double *a, *b; int dim; { int i;  for ( i=0; i<dim; i++)   b[i] =a[i]; }

While the invention has been described by way of example embodiments, itis understood that the words which have been used herein are words ofdescription, rather than words of limitation. Changes may be made,within the purview of the appended claims, without departing from thescope and spirit of the invention in its broader aspects. Although theinvention has been described herein with reference to particularstructures, materials, and embodiments, it is understood that theinvention is not limited to the particulars disclosed. Rather, theinvention extends to all appropriate equivalent structures, mechanisms,and uses.

1. (canceled)
 2. A method of calculating an estimated trueelectrocardiogram (ECG) signal from a patient undergoing cardiopulmonaryresuscitation (CPR), said patient having a chest, said method comprisingthe steps of: applying CPR to the chest of a patient and measuring avalue corresponding to CPR, said value selected from a group consistingof force associated with CPR, displacement of the chest during CPR,velocity of the chest during CPR, motion of a CPR device administeringCPR and combinations thereof; providing the measured value correspondingto CPR as a first input to a processor; providing a measured ECG signalas a second input to the processor; and processing the first input andthe second input with the processor to produce an estimated true ECGsignal.
 3. The method of claim 2 wherein the step of processing thefirst and second inputs is performed using a non-linear method.
 4. Themethod of claim 2 wherein the step of processing the first and secondinputs is performed using linear predictive filtering.
 5. The method ofclaim 2 wherein the step of processing the first and second inputs isperformed using the method of recursive least squares.
 6. A system forfacilitating the effective administration of cardiopulmonaryresuscitation (CPR), said system comprising: an accelerometer forproducing an acceleration signal indicative of the displacement of a CPRrecipient's chest; a housing for holding the accelerometer in fixedrelationship to the chest as it moves in response to CPR compressions; amicroprocessor programmed to process the acceleration signal todetermine the depth of chest compression and produce a compressionsignal indicative of the depth of compression of the patient's chest,said microprocessor further programmed to determine the start of acompression without reference to a signal derived from a source not heldin fixed relationship to the chest and thereafter calculate downwarddisplacement of the chest using the acceleration signal.
 7. The systemof claim 6 further comprising: a signaling mechanism, said signalingmechanism operable to produce a signal indicative of the displacement ofthe chest and operably connected to the microprocessor, wherein themicroprocessor is further programmed to operate the signaling mechanismto indicate when the displacement value of the chest is within a desiredrange.